Mistral AI · model passport
Mistral: Mistral Large 4
mistral-large-4-0- 1,048,576 context
- Best percentile
- 89.0AIME (math)
- Composite standing
- 55.1shrunk · 3/27 axes
What the data says
Benchmarked on 3 of 27 tracked axes. Every figure below is the model's own published result on that board.
Strongest axes
- 89 pct — AIME (math) (98.3%)
Uneven: 73.1 percentile points between its best and worst axis — 89 pct on AIME (math) versus 15.9 pct on SimpleQA Verified.
- AIME (math)89 pct98.3%Verify →
- GPQA Diamond76 pct88.1%Verify →
- SimpleQA Verified15.9 pct20.0%Verify →
- OverallNot benchmarked
- WebDev ArenaNot benchmarked
- Vision ArenaNot benchmarked
- Factuality ArenaNot benchmarked
- Search ArenaNot benchmarked
- Document ArenaNot benchmarked
- Agent ArenaNot benchmarked
- FrontierMathNot benchmarked
- ARC-AGI-2Not benchmarked
- Humanity's Last ExamNot benchmarked
- SimpleBenchNot benchmarked
- LiveBenchNot benchmarked
- BFCL v4 (function calling)Not benchmarked
- SWE-bench Verified (live board)Not benchmarked
- Terminal-Bench 4.0Not benchmarked
- MMLU-Pro (Artificial Analysis)Not benchmarked
- LiveCodeBench (Artificial Analysis)Not benchmarked
- IFBench (Artificial Analysis)Not benchmarked
- HHEM Hallucination (Vectara)Not benchmarked
- SWE-bench VerifiedNot benchmarked
- Terminal-BenchNot benchmarked
- CodingNot benchmarked
- Instruction followingNot benchmarked
- Hard promptsNot benchmarked
Percentiles are the model's standing within each board's own population. Axes marked "not benchmarked" have no published result for this model — that is an absence of data, not a low score.
How to run it
Use it hosted
mistralai/mistral-large-4-0API parameters this endpoint supports
Example request
curl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"mistralai/mistral-large-4-0","messages":[{"role":"user","content":"Hello"}]}'Identifiers, limits and prices are synced from the upstream source shown above. Any field we haven't synced is left out entirely rather than guessed.
mistral-large-4-0 stands at 55.1 (raw mean 60.3) — measured on 3 of 27 axes.
mistral-large-4-0 scores in the 89th percentile on AIME (math).
mistral-large-4-0 ranks between #55 and #288 across 4 built-in weightings — best under "Reasoning", worst under "Conversation-first".
Every claim is a computed fact from the current board data, phrased by a low-temperature model call and rejected by a validation gate if any number is not in the source row. How the leaderboards work →